An important branch of voice recognition technology is the wake-on-voice technology which can judge whether a user says a specified wake-up word to start a device by monitoring the user's voices. At present, the wake-on-voice technology has played an important part in fields such as vehicle-mounted system, navigation and smart home, and used to start an application or a service by voice.
The existing wake-on-voice methods mainly rely on a junk word network to realize the wake-on-voice, i.e., the final recognized results may be obtained by selecting some junk words and wake-up words to build a recognition network. A junk word may refer to a word used indiscriminately or excessively.
However, the wake-on-voice technology needs to monitor voices for a long time, i.e., it is required to turn on a recording device and maintain the recording device in an operating and computing condition for a long time. For the existing wake-on-voice technology, the structures of the recognition network and the wake-up network are complicated and the computation burden during the voice activity detection, decoding process or the like is massive, such that the power consumption of device is high and the requirement for long-time monitoring voice cannot be satisfied, thus reducing the processing performance.